Diffusion-weighted Imaging of Lymph Node Tissue

Purpose: The study investigates the hypothesis of clinically observed decreased apparent diffusion coefficient (ADC) of cancerous lymph nodes can be attributed to increased cellularity. The study characterises the mean diffusivity (MD) of lymph node sub-structures and investigates correlation between MD and cellularity metrics. The study also investigates the theoretical information content of single and multi-biophysical models. Methods:. A 3 mm diameter core sample was extracted from a formalin fixed lymph node tissue post-surgery and imaged using 9.4T and 16.4T Bruker MRI system. Samples were sectioned and stained with haematoxylin and eosin (H&E). Diffusion tensor model was fitted voxelwise and MD values were computed using Matlab. Cellularity metrics includes measurement of nuclear count and nuclear area. Eleven models with combinations of isotropic, anisotropic, and restricted components were tested for diffusion modelling and ranked using the Akaike information criterion (AIC). Results: The findings showed distinct diffusivities of lymph node sub-structures (capsule and parenchyma). Parenchyma in normal lymph node tissues had higher MD (0.71 ± 0.17 µm2/ms) than metastatic parenchyma (0.52 ± 0.08 µm2/ms) and lymphoma (0.47 ± 0.19 µm2/ms). No correlation were observed between MD and nuclear count (r = 0.368) and nuclear area (r = 0.368) respectively at 95 % confidence intervals. The single biophysical models (ADC and DTI) were ranked lowest by AIC. Multi-biophysical models consist of anisotropic and restricted diffusion (Zeppelin-sphere, Ball-stick-sphere, and Ball-sphere) were ranked highest in the majority of voxels of the tissue samples. Conclusion: A distinct diffusivity value were found in lymph node sub-structures with no correlation to cellularity. Multi-biophysical models were ranked highest and extract more information from the measurement data than simple single biophysical models